Comparative genomics promises to shed light on those genetic changes that gave rise to the modern human species. Mounting evidence suggests that the vast majority of functional differences between the human and chimpanzee genomes are in regions that do not code for proteins. Focusing on these non-coding regions, we will investigate lineage-specific evolution in the human genome. Our approach includes developing likelihood ratio tests for identifying changes in either the rate or the pattern of nucleotide substitution in a single lineage. These novel methods will be implemented in open source software that can be used to scan an entire genome. We will apply this evolutionary analysis to multiple sequence alignments of human and other vertebrates, including several closely related species (macaque, chimpanzee, Neanderthal), allowing us to identify recent changes in the human genome. In order to concentrate on functionally relevant changes, evolutionary testing will be limited to sets of candidate regions with specific known or predicted functions (e.g. regulatory regions, RNA genes). Predicted functional regions will be identified using machine learning classification techniques. These classifiers will employ measures of sequence conservation as well as the rapidly expanding collection of experimental and bioinformatic annotations of the human genome, including results of the ENCODE Project and other functional genomic studies. After identifying those regions that were most significantly altered in the human lineage, we will use this functional information to develop testable hypotheses about the effects of the observed changes. Experimental investigations of these genomic regions will lead to new understanding of the evolution of human biology and health. [unreadable] [unreadable] PROJECT NARRATIVE: This project will vastly expand knowledge of biologically relevant features of the human genome that are unique to our species. Identification and characterization of the genetic changes leading to modern humans is of fundamental interest. These investigations also promise to contribute to our understanding of the causal mechanisms behind human diseases, leading to directed treatment and prevention strategies. [unreadable] [unreadable] [unreadable]